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One day. Twenty four hours. Every single day, people must decide how to split up the twenty four hours they are given. Our goal for this project was to determine how a person’s time usage is related to various factors such as wellbeing, intelligence, success, and happiness. Analyzing this data provides information about what people can do to make the most of their time. Although we didn’t focus on it for this project, analyzing the amount of time spent on different activities per day can also increase awareness to what can feasibly be done in one day, making it useful for time management and scheduling.

General Data

The above choropleths make it easy to visualize general statistics regarding IQ, obesity, and GDP per capita that we used in our project. Further down, we will look for correlations between these statistics and the time spent on relevant activities.

Male vs. Female

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IQ

Obesity

The above plots explore the relationships between the time spent sleeping, exercising, eating, and partaking in leisure versus obesity rates. There seems to be a relatively strong correlation between time spent sleeping and obesity rates. A greater amount of time spent asleep could indicate laziness and an increased risk of obesity. On the other hand, there seems to be a relatively strong negative relationship between time spent exercising and obesity rates. This makes sense- the more a person exercises, the less likely they are going to be overweight. Surprisingly, there also seems to be a negative relationship between time spent eating and obesity rates. But breaking it down, this does make sense. Eating slower is associated with eating less, which results in less weight gain. When people are busy, they tend to go for unhealthy, fast food options that can be eaten on-the-go, which results in weight gain. In addition, many countries whose cultures are largely based around food (and socializing during meal time) also place great emphasis on staying active. There is also a negative correlation between leisure time and obesity rates. This also makes sense- more leisure time typically equals less stress, more time to take care of oneself, eat healthy, exercise, and sleep, all of which equal less weight gain.

Wealth

GDP per capita is calculated by dividing a country’s gross domestic product by the population. It is used to determine the country’s standard of living. We were interested in whether the average amount of leisure time in a day plays a role in the prosperity of a nation. According to the plot, it seems that there is very little correlation between these two variables. The coefficient of determination of the linear regression model is 0.030577, which implies a very weak relationship.

Similarly, we were interested in whether the average amount of time spent working each day played a role in a nation’s prosperity. According to the plot, it again appears there is very little correlation between these two variables. The coefficient of determination of the linear regression model is 0.025327, which implies a very weak relationship.

Time Use Analysis

General Data

Male vs. Female

IQ

Obesity

Wealth

Life Expectancy

Life Satisfaction

Gender: Life Expectancy vs. Satisfaction